Regression lines pass as close as possible {best fit}| to all points and so minimize sum of distances from points to regression line. Lines can pass closest to points if sum of squares of differences from line to points is minimum. Best-fit lines must pass through all property means: x2 = m * x1 + b, where x1 and x2 are means, m is slope, and b is y-intercept. m = (N * (sum from i = 1 to i = N of n1(i) * n2(i)) - (sum from i = 1 to i = N of n1(i)) * (sum from i = 1 to i = N of n2(i))) / (N * (sum from i = 1 to i = N of n1(i)^2) - (sum from i = 1 to i = N of n1(i)^2)). b = x2 - m * x1.
Mathematical Sciences>Statistics>Correlation>Regression
3-Statistics-Correlation-Regression
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Date Modified: 2022.0224